Control of seismically excited vibration using electrorheological materials and Lyapunov methods

Gavin, Henri P.

doi:10.1109/87.896743

Cited by 60 publications

(46 citation statements)

References 32 publications

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“…2 . Especially the fairly better control performance on the absolute acceleration of each floor is achieved with the predictive semi-active control compared to that achieved with the he semi-active control law proposed in (Gavin, 2001). This result indicates that the importance of the proposed integrated design approach, i.e., the design of the structural system (the control object) with taking the employed control law into consideration.…”

Section: Design Examplementioning

confidence: 82%

“…str.)) shows the better performance on vibration suppression compared to that of the semi-active control proposed by (Gavin, 2001) (Energy-based SA (Opt. str.))…”

Section: Design Examplementioning

confidence: 99%

“…• The damping coefficient of the semi-active damper is determined so as to maximally accelerate energy dissipation of the structural systems (Gavin, 2001).…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Semi-Active Control of Civil Structures Based on the Prediction of the Structural Response: Integrated Design Approach

Hiramoto¹,

Matsuoka²,

Sunakoda³

2011

Vibration Analysis and Control - New Trends and Developments

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Section: Design Examplementioning

confidence: 82%

“…str.)) shows the better performance on vibration suppression compared to that of the semi-active control proposed by (Gavin, 2001) (Energy-based SA (Opt. str.))…”

Section: Design Examplementioning

confidence: 99%

See 1 more Smart Citation

Semi-Active Control of Civil Structures Based on the Prediction of the Structural Response: Integrated Design Approach

Hiramoto¹,

Matsuoka²,

Sunakoda³

2011

Vibration Analysis and Control - New Trends and Developments

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“…The purpose of the method was not to decrease the amplitude of system vibration, as many researchers have sought to accomplish in the past (Karnopp et al, 1974;Gavin, 2001), but rather to increase it. In the aforementioned study, the variable damping coefficient was harmonically varied.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of Semi-Active Control using Harmonically Varying Damping by Real-Time Hybrid Simulation

Iba

Phillips

Spencer

2012

JSDD

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This study demonstrates the efficiency of a new semi-active vibration control method validated using real-time hybrid simulation considering a single-degree-of-freedom system. The semi-active control method treated in this study is based on harmonically varying damping. Even if the input to the system doesn't contain the natural frequency of the system, it is possible to choose the frequency of the damping coefficient so that the response includes the natural frequency. As a result of this operation, resonance can be induced, with the phase and amplitude of the resonance adjustable through the damping parameters. Previous study proposed a new vibration control method to take advantage of harmonically varying damping. In the case that the excitation contains the natural frequency of the system, resonance is induced. At the same time, if the additional harmonic vibration induced by the variable damping is at the same frequency of the resonance yet anti-phase, the resonance can be reduced by interference. An expression for the variable damping controller has been developed in the case of an ideal variable damping device and control performance has been confirmed by numerical simulation. However, the control method does not directly apply to actual variable damping devices, because the control laws determine the ideal variable damping ratio, neglecting any nonlinearities of actual damping devices. In this study, the proposed theory has been modified to fit a magneto-rheological (MR) damper. Validation of the modification was performed experimentally using real-time hybrid simulation.

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“…Moreover, semiactive control is simple, has low energy consumption, and is safe against failure of the control element compared to active control that is realized by sensors, a (feedback) controller, and actuators requiring a large power supply. Because of the above advantages, semiactive control has been actively studied as a vibration control method for structural systems subject to large-scale earthquake disturbances in which surrounding power failure can be occurred [1][2][3][4][5].…”

Section: Introductionmentioning

confidence: 99%

Adaptive Gain Scheduled Semiactive Vibration Control Using a Neural Network

Hiramoto¹,

Matsuoka²,

Sunakoda³

2018

Shock and Vibration

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We propose an adaptive gain scheduled semiactive control method using an artificial neural network for structural systems subject to earthquake disturbance. In order to design a semiactive control system with high control performance against earthquakes with different time and/or frequency properties, multiple semiactive control laws with high performance for each of multiple earthquake disturbances are scheduled with an adaptive manner. Each semiactive control law to be scheduled is designed based on the output emulation approach that has been proposed by the authors. As the adaptive gain scheduling mechanism, we introduce an artificial neural network (ANN). Input signals of the ANN are the measured earthquake disturbance itself, for example, the acceleration, velocity, and displacement. The output of the ANN is the parameter for the scheduling of multiple semiactive control laws each of which has been optimized for a single disturbance. Parameters such as weight and bias in the ANN are optimized by the genetic algorithm (GA). The proposed design method is applied to semiactive control design of a base-isolated building with a semiactive damper. With simulation study, the proposed adaptive gain scheduling method realizes control performance exceeding single semiactive control optimizing the average of the control performance subject to various earthquake disturbances.

show abstract

Control of seismically excited vibration using electrorheological materials and Lyapunov methods

Cited by 60 publications

References 32 publications

Semi-Active Control of Civil Structures Based on the Prediction of the Structural Response: Integrated Design Approach

Semi-Active Control of Civil Structures Based on the Prediction of the Structural Response: Integrated Design Approach

Evaluation of Semi-Active Control using Harmonically Varying Damping by Real-Time Hybrid Simulation

Adaptive Gain Scheduled Semiactive Vibration Control Using a Neural Network

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